Analysis of Spatiotemporal Characteristics and Influencing Factors of Land Urbanization Level in China at Different Scales Based on Nighttime Light Remote Sensing

被引:2
|
作者
Zhang, Zhaoxu [1 ]
Liu, Xingchi [1 ]
Li, Jiayi [1 ]
Fu, Shihong [1 ]
Sun, Yuanheng [2 ]
Qiao, Rongfeng [1 ]
机构
[1] Tiangong Univ, Sch Environm Sci & Engn, Tianjin 300387, Peoples R China
[2] Dalian Maritime Univ, Environm Informat Inst, Nav Coll, Dalian 116026, Peoples R China
关键词
Urban areas; Remote sensing; Economics; Data mining; Economic indicators; Artificial light; Reliability; Nighttime light remote sensing; scale; spatiotemporal analysis; urbanization; IMAGES; CITY;
D O I
10.1109/JSTARS.2024.3390985
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Urbanization is an important symbol of regional economic development and social progress. Studying the urbanization level is greatly important for the scientific development of towns and cities, and for the efficient decision-making of governments. The nighttime light data, which encompasses valuable insights into human activities, economic progress, and social development, effectively addresses the limitations associated with the indicator method in terms of uncertainty and lag issues. Those data can also provide a more intuitive reflection of the level of urbanization and offer novel insights for research on urbanization. In this study, based on the 2000-2020 EANTLI_Like nighttime light remote sensing data, the characteristics of the spatial and temporal dynamic changes in the land urbanization level in China were measured. Results were analyzed at four scales: national, regional, provincial, and municipal. Finally, the main economic indicators affecting urbanization were selected as variables to simply analyze the driving force of land urbanization through spatial autocorrelation and spatiotemporal geographically weighted regression model. Results indicated that China's land urbanization level continued to grow from 2000 to 2020, with an average annual growth rate of 2.51%. The spatial distribution of land urbanization varied significantly across regions. The level of land urbanization in the eastern coastal region was significantly higher than that in the inland and western provinces, at the agricultural and provincial scales. Hong Kong, Macao, and Shanghai ranked high in terms of land urbanization, and the Pearl River Delta and Yangtze River Delta regions in which they were located also belong to the cluster of high land urbanization levels. Meanwhile, the goodness of fit among GDP, the proportion of output of secondary and tertiary industries, freight volume, and land urbanization level were higher than 0.86. Among them, GDP and the output of secondary and tertiary industries had a more obvious role in promoting land urbanization. The freight volume exhibited positive effects on land urbanization level in the western region, Heilongjiang, and Jilin provinces. This study is very important for understanding the law of urban construction land expansion in China, the regional differences in land urbanization level, and the optimization of land use layout.
引用
收藏
页码:9811 / 9827
页数:17
相关论文
共 50 条
  • [1] Spatiotemporal Analysis and Prediction of Carbon Emissions from Energy Consumption in China through Nighttime Light Remote Sensing
    Zhang, Zhaoxu
    Fu, Shihong
    Li, Jiayi
    Qiu, Yuchen
    Shi, Zhenwei
    Sun, Yuanheng
    REMOTE SENSING, 2024, 16 (01)
  • [2] Spatiotemporal Characteristics of Urbanization in the Taiwan Strait Based on Nighttime Light Data from 1992 to 2020
    Ye, Yuqing
    Yun, Guoliang
    He, Yuanrong
    Lin, Ruijin
    He, Tingting
    Qian, Zhiheng
    REMOTE SENSING, 2023, 15 (13)
  • [3] RESEARCH ON THE DEVELOPMENT OF URBANIZATION IN YANGTZE RIVER ECONOMIC BELT BASED ON NIGHTTIME LIGHT REMOTE SENSING DATA
    Zhang, Wei
    Qi, Jianwei
    Wang, Guanghui
    Zhang, Tao
    Zhai, Haoran
    IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2020, : 4426 - 4429
  • [4] The Spatial Pattern and Influencing Factors of China's Nighttime Economy Utilizing POI and Remote Sensing Data
    Yan, Guodong
    Zou, Lin
    Liu, Yunan
    APPLIED SCIENCES-BASEL, 2024, 14 (01):
  • [5] Nighttime light remote sensing reveals the pattern and process of urbanization evolution in northwest China since the 21st century
    Liu S.
    Chen Z.
    Shi K.
    Wu B.
    Wei Y.
    Wang C.
    Li X.
    Wu J.
    Yu B.
    National Remote Sensing Bulletin, 2024, 28 (06) : 1497 - 1514
  • [6] Analysis of evapotranspiration characteristics for different land covers over Songnen Plain based on remote sensing
    Zeng L.
    Song K.
    Zhang B.
    Wang Z.
    Du J.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2010, 26 (09): : 233 - 242
  • [7] Spatiotemporal characteristics and influencing factors of renewable energy production in China: A spatial econometric analysis
    Xu, Jie
    Lv, Tao
    Hou, Xiaoran
    Deng, Xu
    Li, Na
    Liu, Feng
    ENERGY ECONOMICS, 2022, 116
  • [8] Dynamic Characteristics of Urbanization Based on Nighttime Light Data in China's "Plain-Mountain Transition Zone"
    Li, Tingting
    Guo, Zengzhang
    Ma, Chao
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (15)
  • [9] Is potential cultivated land expanding or shrinking in the dryland of China? Spatiotemporal evaluation based on remote sensing and SVM
    Cai, Liping
    Wang, Hui
    Liu, Yanxu
    Fan, Donglin
    Li, Xiaoxiao
    LAND USE POLICY, 2022, 112
  • [10] Long-Term Spatiotemporal Characteristics and Impact Factors of Land Surface Temperature of Inhabited Islands with Different Urbanization Levels
    Zhang, Junmao
    Lin, Tao
    Sun, Caige
    Lin, Meixia
    Zhan, Yulin
    Chen, Yuan
    Ye, Hong
    Yao, Xia
    Huang, Yiyi
    Zhang, Guoqin
    Liu, Yuqin
    REMOTE SENSING, 2022, 14 (19)